class_docstr: Class for the manifold of geometric distributions.
  
  This is the parameter space of geometric distributions
  i.e. [0,1] segment.
docstr: Sample from the geometric distribution.
  
  Sample from the geometric distribution with parameter provided
  by point.
  
  Parameters
  ----------
  point : array-like, shape=[..., 1]
      Point representing an geometric distribution.
  n_samples : int
      Number of points to sample with each parameter in point.
      Optional, default: 1.
  
  Returns
  -------
  samples : array-like, shape=[..., n_samples]
      Sample from geometric distributions.
docstr_tok: ["Sample","from","the","geometric","distribution",".","Sample","from","the","geometric","distribution","with","parameter","provided","by","point",".","Parameters","--","--","--","--","--","point",":","array-like",",","shape=","[","...",",","1","]","Point","representing","an","geometric","distribution",".","n_samples",":","int","Number","of","points","to","sample","with","each","parameter","in","point",".","Optional",",","default",":","1",".","Returns","--","--","--","-","samples",":","array-like",",","shape=","[","...",",","n_samples","]","Sample","from","geometric","distributions","."]
code: def sample(self, point, n_samples=1):
      """Sample from the geometric distribution.
  
      Sample from the geometric distribution with parameter provided
      by point.
  
      Parameters
      ----------
      point : array-like, shape=[..., 1]
          Point representing an geometric distribution.
      n_samples : int
          Number of points to sample with each parameter in point.
          Optional, default: 1.
  
      Returns
      -------
      samples : array-like, shape=[..., n_samples]
          Sample from geometric distributions.
      """
      return self._scp_rv.rvs(point, n_samples)
  
imports: from scipy.stats import geom
  import geomstats.backend
  from geomstats.geometry.base import VectorSpaceOpenSet
  from geomstats.geometry.euclidean import Euclidean
  from geomstats.geometry.riemannian_metric import RiemannianMetric
  from geomstats.information_geometry.base import InformationManifoldMixin, ScipyUnivariateRandomVariable
label_desc: Use image node_id 6 for calling the GeometricDistributions obj's underlying member method code with example usage: obj.sample(point, n_samples) and returns: self